Automated segmentation of liver and hepatic vessels on portal venous phase computed tomography images using a deep learning algorithm.

ABSTRACT:

Background

CT-image segmentation for liver and hepatic vessels can facilitate liver surgical planning. However, time-consuming process and inter-observer variations of manual segmentation have limited wider application in clinical practice.

Purpose

Our study aimed to propose an automated deep learning (DL) segmentation algorithm for liver and hepatic vessels on portal venous phase CT images.

Methods

This retrospective study was performed to develop a coarse-to-fine DL-based algorithm that was trained, validated, and tested using private 413, 52, and 50 portal venous phase CT images, respectively. Additionally, the performance of the DL algorithm was extensively evaluated and compared with manual segmentation using an independent clinical dataset of preoperative contra

SUBMITTER: Li S 

PROVIDER: S-EPMC11302809 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature